39 citations · 155 across the 29 of their papers we have counts for
5 papers · 2 filters
Unified recurrent neural network for many feature types
Alexander Stec, Diego Klabjan, Jean Utke
There are time series that are amenable to recurrent neural network (RNN) solutions when treated as sequences, but some series, e.g. asynchronous time series, provide a richer vari…
Nested multi-instance classification
Alexander Stec, Diego Klabjan, Jean Utke
There are classification tasks that take as inputs groups of images rather than single images. In order to address such situations, we introduce a nested multi-instance deep networ…
Forecasting Crime with Deep Learning
Alexander Stec, Diego Klabjan
The objective of this work is to take advantage of deep neural networks in order to make next day crime count predictions in a fine-grain city partition. We make predictions using…
Bayesian active learning for choice models with deep Gaussian processes
Jie Yang, Diego Klabjan
In this paper, we propose an active learning algorithm and models which can gradually learn individual's preference through pairwise comparisons. The active learning scheme aims at…
Improved Classification Based on Deep Belief Networks
Jaehoon Koo, Diego Klabjan
For better classification generative models are used to initialize the model and model features before training a classifier. Typically it is needed to solve separate unsupervised…